• Journal of Distribution Science
• /
• v.16 no.5
• /
• pp.91-101
• /
• 2018

Purpose - This study compares the management efficiency of retailers in China, Korea and other global countries. China's retail industry is experiencing a recession. In order to strengthen the competitiveness of retailers, it is necessary to manage the efficiency. Therefore, we analyzed the management efficiency of Chinese retailers as well as Korea and global retailers who are competing with Chinese retailers. Research design, data, and methodology - The DEA(Data Envelopment Analysis) carried out for evaluating the relative efficiency of multiple DMUs (decision making units) with homogeneity. Data were collected from the American Retail Trade Association (2017). In those distributors' data, 5 of China and 5 of Korea and 10 of other global countries' analyzed. CCR and BCC analysis were performed to determine the cause of the inefficiency of DMUs by measuring the technical efficiency, pure technology efficiency and scale efficiency. Result - Among the 20 retail distributors, Costco, Kroger (Global), Eland World, BGF(Korea) are operating efficiently. Chinese retailers are operating inefficiently. Retailers' CRS status means the growth rate of input is equal to the growth rate of output. In the case of DRS status, the ratio of output to input variable is much smaller. In order to improve inefficiency, reducing input variables can be a solution. For the firms in IRS status, the rate of increase in output is relative greater than the input. That means efficiency is good condition. The analysis result shows that most retailers are showing DRS status especially Chinese retailers. Scale efficiency is a major cause of inefficiency rather than pure technology efficiency. It is recommended for ineffective retailers to reduce inputs to become efficient retailers. Otherwise, retrain existing employees or introducing advanced technologies to increase the output. Conclusions - Most of Chinese retailers are operating inefficiently which caused by the excessive investment in the inputs. On the other hand, Other global retailers are analyzed to be efficient by DEA. In this study, benchmarking targets of some retailers' suggested to improve the management efficiency especially in inputs.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.37 no.4
• /
• pp.239-244
• /
• 2014

The conventional clustering approaches are mostly based on minimizing total dissimilarity of input and output. However, the clustering approach may not be helpful in some cases of clustering decision making units (DMUs) with production feature converting multiple inputs into multiple outputs because it does not care converting functions. Data envelopment analysis (DEA) has been widely applied for efficiency estimation of such DMUs since it has non-parametric characteristics. We propose a new clustering method to identify groups of DMUs that are similar in terms of their input-output profiles. A real world example is given to explain the use and effectiveness of the proposed method. And we calculate similarity value between its result and the result of a conventional clustering method applied to the example. After the efficiency value was added to input of K-means algorithm, we calculate new similarity value and compare it with the previous one.

• Journal of Climate Change Research
• /
• v.7 no.1
• /
• pp.59-68
• /
• 2016

The world's major countries have focused on the renewable energy industry as the solution to climate change and the energy crisis. Nevertheless, there are no studies on the economic effects of the renewable energy industry. This study analyzed the economic effects of Korea's renewable energy industry by using the 2010 Input-Output Table. It is estimated that Korea's renewable energy industry made a production-induced effect of 2.0262 won, and a value-added-induced effect of 0.6138 won through an increase in output growth of 1 won, and an employment-induced effect of 2.3046 labors through an increase in output growth of 1 billion won. Both the effect ratio and the response ratio were greater than 1, which means the renewable energy industry is an intermediate manufacturing industry whose forward linkage effect and backward linkage effects are large. These results show differences with previous studies that classified electricity sector and renewable energy industry into final primary production industries. It is expected that the economic effects of the renewable energy industry will become greater in the future. Therefore, research on statistics related to the renewable energy industry is needed for more precise analysis.

• Journal of Contemporary Eastern Asia
• /
• v.23 no.1
• /
• pp.58-82
• /
• 2024

Former South Korean President Moon Jae-in implemented a project called the Peace Initiative, which prioritized a "peaceful and prosperous Korean Peninsula" as the core national agenda and involved using a peace-based frame instead of a unification approach to address inter-Korean relations from a different perspective. This initiative was evaluated in this study using a revised version of the pyramid model to assess the input-output-result process underlying the project and determine whether it generated results that differed from those achieved by the previous administration. To these ends, this research compared Moon's key presidential speeches with those of his predecessor, Park Geun-hye, as input, news commentaries and responses from major players as output, and the trend of perceptional and attitudinal changes in public opinion as results. Although Moon failed to accomplish significant policy effects on inter-Korean relations because of geopolitical challenges and the transfer of power to the conservative party, the analysis revealed that the input, output, and partial results of inter-Korean dialogue reflect some progress.

• Journal of Distribution Science
• /
• v.19 no.7
• /
• pp.29-39
• /
• 2021

Purpose: As China experienced a crisis due to Covid-19, the global supply chain collapsed and affected the world. Therefore, it is time for a change in port operational efficiency, increasing in importance with changes in the global supply chain. This study analyzed Shanghai Port's efficiency, the world's largest port and representative hub port in Northeast Asia, by looking at the relationship between facility factors and cargo throughput to present hub port development's timely implications. Research design, data and methodology: This study applied the Charnes, Cooper, and Rhodes (CCR) and Banker, Chames, and Cooper (BCC) models of the data development analysis (DEA) to construct an analysis from the input-oriented and output-oriented perspectives. Results: As a result, Yidong Container Terminal can be considered the most optimized in facilities and operation processes. Yidong and Shengdong Container Terminal should maintain current operating levels, while Pudong Container Terminal should review facility investments. Also, Zhendong, Huong, Mingdong, and Guandong Container Terminal should be reviewed to increase cargo throughput or to adjust current input variables in the current state. Conclusions: Therefore, the utilization of the container terminal input variables should be reviewed, and the factors of inefficiency should be improved. Moreover, the strategic focus of container terminal operations should be on increasing annual cargo throughput.

• Journal of Korea Multimedia Society
• /
• v.23 no.8
• /
• pp.915-926
• /
• 2020

Outlier detection methods help one to identify unusual instances in data that may correspond to erroneous, exceptional, or surprising events or behaviors. This work studies conditional outlier detection, a special instance of the outlier detection problem, in the context of incorrect data label identification. Unlike conventional (unconditional) outlier detection methods that seek abnormalities across all data attributes, conditional outlier detection assumes data are given in pairs of input (condition) and output (response or label). Accordingly, the goal of conditional outlier detection is to identify incorrect or unusual output assignments considering their input as condition. As a solution to conditional outlier detection, this paper proposes the ratio-based outlier scoring (ROS) approach and its variant. The propose solutions work by adopting conventional outlier scores and are able to apply them to identify conditional outliers in data. Experiments on synthetic and real-world image datasets are conducted to demonstrate the benefits and advantages of the proposed approaches.

• Transactions of Materials Processing
• /
• v.12 no.2
• /
• pp.110-115
• /
• 2003

This paper is concerned with the compression test and forming process of flange by using virtual reality and analysis(simulation) program. This virtual manufacturing can be carried out one personal computer without any expensive devices for experiment. The virtual manufacturing composed of three modules such as the imput, calculation and the output modules on internet. Internet user can give the material's property and process parameters to the sever computer at the input module. On the calculation module, a simulator computes the virtual manufacturing process by analysis program and stores the data as a file. The output module is the program in which internet user can confirm virtual manufacturing results by showing tables, graphs, and 3D animation. This programs is designed by an internet language such as HTML, CGI, VRML and JAVA ,while analysis programs use the finite increasing, the virtual manufacturing technique will substitute many real experiments in the future.

• Journal of Technology Innovation
• /
• v.16 no.2
• /
• pp.65-94
• /
• 2008

There has been rapid diffusion of digital innovation technology(DIT) such as 3 D CAD, CAE, simulation software which enable firms to see the future results of intended product designs through 3 D diagram and simulated results. This technology helps firms to reduce trial and error process by solving later stage problems in earlier stages. The DIT being the technology reflecting the real world, as a tool representing the simplified form of the real world, the degree of reflecting the real world(fidelity) is important in utilizing the DIT. This study is an exploratory research examining the process of reviewing the fidelity of the DITs and developing the complementary process necessary for utilizing the DIT with 'not good enough' fidelity. This study could draw out, from its case study, an exploratory hypothesis about the process of developing the complementary process. In the process, there is an analysis of the corresponding relationship between the actual data and the output data of the DIT, e.g. simulated result. Then the input data or output data are adjusted on the basis of the analysis of the corresponding relationship so that the discrepancy between the actual data and the expected interpretation of the output data, through the adjustment, of the DIT, can be reduced. This process is sometimes accompanied by the process of generating experimental data, which reflect the unique situation of the product development process of a company, to be put to the data base of DIT. The complementary process is the process requiring knowledge sharing and adjustment activities across different divisions. This study draw outs implications for effective management of the fidelity of DIT tools.

• Journal of Information Processing Systems
• /
• v.18 no.2
• /
• pp.268-281
• /
• 2022

The development of information technology is bringing many changes to everyday life, and machine learning can be used as a technique to solve a wide range of real-world problems. Analysis and utilization of data are essential processes in applying machine learning to real-world problems. As a method of processing data in machine learning, we propose an approach based on applying multiple linear regression models by interlacing data to the task of classifying similar software. Linear regression is widely used in estimation problems to model the relationship between input and output data. In our approach, multiple linear regression models are generated by training on interlaced feature data. A combination of these multiple models is then used as the prediction model for classifying similar software. Experiments are performed to evaluate the proposed approach as compared to conventional linear regression, and the experimental results show that the proposed method classifies similar software more accurately than the conventional model. We anticipate the proposed approach to be applied to various kinds of classification problems to improve the accuracy of conventional linear regression.

• Korea Real Estate Review
• /
• v.27 no.4
• /
• pp.51-61
• /
• 2017

The purpose of this study is to find out the implications for the activation of the real estate industry by comparing the structure of production and distribution, as well as the industrial linkage, of Korean real estate industry with that of the US through an input-output analysis. This study employed the World Input-Output Database (WIOD) provided by the EU in 2016. The results are as follows. First, while the share of the Korean real estate industry in the national economy has been steadily decreasing since the year 2000, the real estate industry of the United States is increasing. Second, both Korean and US real estate businesses have higher value added rates than the industry average, but the intermediate demand rate is lower than the industry average. Furthermore, the intermediate input rate and intermediate demand rate of the Korean real estate industry were lower than that of the US. Third, the change in the final demand for the Korean real estate industry has a lower production and value added effect on the national economy than that of the United States. Fourth, the industrial linkage of the US real estate industry is larger and broader than that of Korea. Finally, it is suggested that a policy to increase the industrial linkage of real estate industry with high value-added industries is needed in order to revitalize Korea's real estate industry.